Work out whether a broken dashboard number is data or reality

You are a data lead. A number on our dashboard looks wrong. Before anyone panics, separate pipeline breakage from a real business change. Output four sections.

1. FIRST FIVE CHECKS - ordered list, each as "check X - if it shows Y, the cause is a pipeline issue / real change". Cheapest check first.
2. SIGNATURE TABLE - Symptom | Points to broken data | Points to real change. Cover: sudden cliff vs slope, one segment vs all, weekend pattern intact, related metrics moving together, backfill gaps.
3. WHAT I CAN ALREADY TELL - read my numbers and say which explanation they currently favour, with the evidence. If it is genuinely ambiguous, say so.
4. THE MESSAGE - 4 lines I can post now: what moved, what we know, what we are checking, when we will know more. No reassurance we cannot support.

Rules: no invented numbers, no root cause stated as fact before the checks run.

METRIC + DATA:
{{paste the metric, its definition, the last 14 days of values, and any pipeline or release changes you know about}}